yolov5返回坐标的方法实例
作者：weixin_44726793
这篇文章主要给大家介绍了关于yolov5返回坐标的相关资料,文中通过实例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下
yolov5返回坐标（v6版）
1 、从yolov5文件夹李找到detect.py，按Ctrl+F 输入annotator.box_label；
if save_img or save_crop or view_img: # Add bbox to image
c = int(cls) # integer class
label = None if hide_labels else (names[c] if hide_conf else f'{names[c]} {conf:.2f}')
annotator.box_label(xyxy, label, color=colors(c, True))
2、找到这个代码后按住ctrl键，鼠标点击box_label，就会跳到plots.py文件并定位到box_label定义的地方；
3、找到p1, p2 = (int(box[0]), int(box[1])), (int(box[2]), int(box[3]))，在这行代码下面新增：
print("左上点的坐标为：(" + str(p1[0]) + "," + str(p1[1]) + ")，右下点的坐标为(" + str(p2[0]) + "," + str(p2[1]) + ")")
4、完成后的代码如下：
def box_label(self, box, label='', color=(128, 128, 128), txt_color=(255, 255, 255)):
# Add one xyxy box to image with label
if self.pil or not is_ascii(label):
self.draw.rectangle(box, width=self.lw, outline=color) # box
if label:
w, h = self.font.getsize(label) # text width, height
outside = box[1] - h >= 0 # label fits outside box
self.draw.rectangle([box[0],
box[1] - h if outside else box[1],
box[0] + w + 1,
box[1] + 1 if outside else box[1] + h + 1], fill=color)
# self.draw.text((box[0], box[1]), label, fill=txt_color, font=self.font, anchor='ls') # for PIL>8.0
self.draw.text((box[0], box[1] - h if outside else box[1]), label, fill=txt_color, font=self.font)
else: # cv2
p1, p2 = (int(box[0]), int(box[1])), (int(box[2]), int(box[3]))
print("左上点的坐标为：(" + str(p1[0]) + "," + str(p1[1]) + ")，右下点的坐标为(" + str(p2[0]) + "," + str(p2[1]) + ")")
cv2.rectangle(self.im, p1, p2, color, thickness=self.lw, lineType=cv2.LINE_AA)5、测试情况：回到命令行，cd到yolov5文件夹，输入指令：python detect.py --source ../mask.1.jpg，其中mask.1.jpg应改为你yolov5文件夹下的图片名称；按回车键后运行就发现输出的信息多了刚才添加的一行
(venv) (base) rongxiao@rongxiao:~/PycharmProjects/yolococo/yolov5$ python detect.py --source ../mask.1.jpg detect: weights=yolov5s.pt, source=../mask.1.jpg, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False YOLOv5 🚀 v6.0-147-g628817d torch 1.8.2+cpu CPU Fusing layers... Model Summary: 213 layers, 7225885 parameters, 0 gradients 左上点的坐标为：(982,384)，右下点的坐标为(1445,767) 左上点的坐标为：(724,237)，右下点的坐标为(770,277) 左上点的坐标为：(711,226)，右下点的坐标为(1689,938) image 1/1 /home/rongxiao/PycharmProjects/yolococo/mask.1.jpg: 384x640 2 persons, 1 airplane, Done. (0.182s) Speed: 1.1ms pre-process, 181.7ms inference, 1.0ms NMS per image at shape (1, 3, 640, 640) Results saved to runs/detect/exp15
附参考：yolov5输出检测到的目标坐标信息（旧版本）
找到detect.py，在大概113行，找到plot_one_box
# Write results
for *xyxy, conf, cls in reversed(det):
if save_txt: # Write to file
xywh = (xyxy2xywh(torch.tensor(xyxy).view(1, 4)) / gn).view(-1).tolist() # normalized xywh
with open(txt_path + '.txt', 'a') as f:
f.write(('%g ' * 5 + '\n') % (cls, *xywh)) # label format
if save_img or view_img: # Add bbox to image
label = '%s %.2f' % (names[int(cls)], conf)
plot_one_box(xyxy, im0, label=label, color=colors[int(cls)], line_thickness=3)ctr+鼠标点击，进入general.py，并自动定位到plot_one_box函数，修改函数为
def plot_one_box(x, img, color=None, label=None, line_thickness=None):
# Plots one bounding box on image img
tl = line_thickness or round(0.002 * (img.shape[0] + img.shape[1]) / 2) + 1 # line/font thickness
color = color or [random.randint(0, 255) for _ in range(3)]
c1, c2 = (int(x[0]), int(x[1])), (int(x[2]), int(x[3]))
cv2.rectangle(img, c1, c2, color, thickness=tl, lineType=cv2.LINE_AA)
print("左上点的坐标为：(" + str(c1[0]) + "," + str(c1[1]) + ")，右下点的坐标为(" + str(c2[0]) + "," + str(c2[1]) + ")")
即可输出目标坐标信息了
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